Beyond network structure: How heterogenous susceptibility modulates the spread of epidemics

摘要

The compartmental models used to study epidemic spreading often assume thesame susceptibility for all individuals, and are therefore, agnostic about theeffects that differences in susceptibility can have on epidemic spreading. Herewe show that--for the SIS model--differential susceptibility can make networksmore vulnerable to the spread of diseases when the correlation between a node'sdegree and susceptibility are positive, and less vulnerable when thiscorrelation is negative. Moreover, we show that networks become more likely tocontain a pocket of infection when individuals are more likely to connect withothers that have similar susceptibility (the network is segregated). Theseresults show that the failure to include differential susceptibility toepidemic models can lead to a systematic over/under estimation of fundamentalepidemic parameters when the structure of the networks is not independent fromthe susceptibility of the nodes or when there are correlations between thesusceptibility of connected individuals.